class_docstr: This class represents a SageMaker trial component object.
  
  A trial component is a stage in a trial.
  Trial components are created automatically within the SageMaker runtime and
  may not be created directly. To automatically associate trial components with
  a trial and experiment, supply an experiment config when creating a job.
  For example: https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTrainingJob.html
  
  Attributes:
      trial_component_name (str): The name of the trial component. Generated by SageMaker
          from the name of the source job with a suffix specific to the type of source job.
      trial_component_arn (str): The ARN of the trial component.
      display_name (str): The name of the trial component that will appear in UI,
          such as SageMaker Studio.
      source (TrialComponentSource): A TrialComponentSource object with a source_arn attribute.
      status (str): Status of the source job.
      start_time (datetime): When the source job started.
      end_time (datetime): When the source job ended.
      creation_time (datetime): When the source job was created.
      created_by (obj): Contextual info on which account created the trial component.
      last_modified_time (datetime): When the trial component was last modified.
      last_modified_by (obj): Contextual info on which account last modified the trial component.
      parameters (dict): Dictionary of parameters to the source job.
      input_artifacts (dict): Dictionary of input artifacts.
      output_artifacts (dict): Dictionary of output artifacts.
      metrics (obj): Aggregated metrics for the job.
      parameters_to_remove (list): The hyperparameters to remove from the component.
      input_artifacts_to_remove (list): The input artifacts to remove from the component.
      output_artifacts_to_remove (list): The output artifacts to remove from the component.
      tags (List[Dict[str, str]]): A list of tags to associate with the trial component.
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docstr: Search Experiment Trail Component.
  
  Returns SearchResults in the account matching the search criteria.
  
  Args:
      search_expression: (SearchExpression): A Boolean conditional statement (default: None).
          Resource objects must satisfy this condition to be included in search results.
          You must provide at least one subexpression, filter, or nested filter.
      sort_by (str): The name of the resource property used to sort the SearchResults
          (default: None).
      sort_order (str): How SearchResults are ordered. Valid values are Ascending or
          Descending (default: None).
      max_results (int): The maximum number of results to return in a SearchResponse
          (default: None).
      sagemaker_session (sagemaker.session.Session): Session object which
          manages interactions with Amazon SageMaker APIs and any other
          AWS services needed. If not specified, one is created using the
          default AWS configuration chain.
  
  Returns:
      collections.Iterator[SearchResult] : An iterator over search results matching the
      search criteria.
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code: def search(
      cls,
      search_expression=None,
      sort_by=None,
      sort_order=None,
      max_results=None,
      sagemaker_session=None,
  ):
      """Search Experiment Trail Component.
  
      Returns SearchResults in the account matching the search criteria.
  
      Args:
          search_expression: (SearchExpression): A Boolean conditional statement (default: None).
              Resource objects must satisfy this condition to be included in search results.
              You must provide at least one subexpression, filter, or nested filter.
          sort_by (str): The name of the resource property used to sort the SearchResults
              (default: None).
          sort_order (str): How SearchResults are ordered. Valid values are Ascending or
              Descending (default: None).
          max_results (int): The maximum number of results to return in a SearchResponse
              (default: None).
          sagemaker_session (sagemaker.session.Session): Session object which
              manages interactions with Amazon SageMaker APIs and any other
              AWS services needed. If not specified, one is created using the
              default AWS configuration chain.
  
      Returns:
          collections.Iterator[SearchResult] : An iterator over search results matching the
          search criteria.
      """
      return super(_TrialComponent, cls)._search(
          search_resource="ExperimentTrialComponent",
          search_item_factory=TrialComponentSearchResult.from_boto,
          search_expression=None
          if search_expression is None
          else search_expression.to_boto(),
          sort_by=sort_by,
          sort_order=sort_order,
          max_results=max_results,
          sagemaker_session=sagemaker_session,
      )
  
file_path: sagemaker-python-sdk/src/sagemaker/experiments/trial_component.py
imports: from __future__ import absolute_import
  import time
  from botocore.exceptions import ClientError
  from sagemaker.apiutils import _base_types
  from sagemaker.experiments import _api_types
  from sagemaker.experiments._api_types import TrialComponentSearchResult
  from sagemaker.utils import format_tags
label_desc: Use image node_id 8 for calling the _TrialComponent obj's underlying member method code with example usage: obj.search(cls, search_expression, sort_by, sort_order, max_results, sagemaker_session) and returns: super